The present disclosure relates to automated systems for tracking and counting objects.
Various automated systems exist for tracking and/or counting objects. For example, currently there are machine learning approaches for detecting people in an area, but they are extremely expensive computationally. Specifically, machine learning is powerful, but high quality classification with few false positives/negatives requires significant processing resources. There are also computer vision approaches, such as simple blob tracking, but they lack accuracy. There are more complex computer vision approaches, however, these approaches demand large amounts of computational resources.
Thus, there is a need in the art for improvements in tracking and counting objects.